Mycobacterium tuberculosis evades immune surveillance during tuberculosis (TB) infection remain complex. Previous studies have found that Mycobacteria can manipulate the miRNAs of host cells to promote their survival during host-pathogen interactions, and most of these effects occur at the cellular miRNA level. We attempted to investigate the possible related mechanisms at the exosomal miRNA level.The mechanisms through which p < 0.05), of which mmu-miR-27b-3p, mmu-miR-93-5p, mmu-miR-25-3p, mmu-miR-1198-5p, mmu-let-7c-5p and let-7a-5p were significantly up-regulated. A bioinformatic analysis indicated that these differentially expressed exosomal miRNAs were involved in multiple biological processes and pathways. The target genes of top six miRNAs in up-regulated groups were positively correlated with the regulation of apoptosis.High-throughput sequencing revealed that Bacillus Calmette-Guérin (BCG) infection could alter the composition of the macrophage exosome content, and the expression levels of miRNAs in exosomes derived from the cell culture media of macrophages showed significant differences between the BCG-infected and non-infected groups. Compared with the non-infected group, 20 exosomal miRNAs were up-regulated and 7 exosomal miRNAs were down-regulated in the infection group (Mycobacterium Bovis Bacillus Calmette-Guérin infection, and the differentially expressed miRNAs were involved in multiple biological processes and signalling pathways. The top six up-regulated miRNAs and their targeted genes were predominantly correlated with the regulation of apoptosis.The expression profile of miRNA in exosomes derived from macrophage were altered after  Mycobacterium tuberculosis complex (MTBC), is the uppermost catastrophic infectious disease that threatens human health and safety. Although the number of newly diagnosed TB decreased from 7.1 million to 5.8 million between 2019 and 2020, there remains 1.3 million HIV-negative individuals and an additional 214,000 HIV-positive individuals died of TB in 2020 [Tuberculosis (TB), mainly caused by the Macrophages act a central role in the innate immunity process because these cells constitute the initial cellular niche for mycobacterial pathogenesis during infection. Through intricate pathogen recognition approaches, macrophages can orchestrate multiple signalling cascades to trigger various innate immune defences including phagocytosis, apoptosis, autophagy and inflammasome activation to eliminate Mtb . MoreoveMicroRNAs (miRNAs) are widely conserved small noncoding RNAs with a length of 18–24 nucleotides that display an indispensable role in many physiological and pathological aspects through the posttranslational regulation of target gene expression . ExosomeThe majority of previous studies focused on differential expression analysis and the functions of miRNAs at the cellular level. However, we attempted to investigate the specific mechanism of immune escape adopted by Mtb based on exosomal miRNA levels by small RNA transcriptome high-throughput sequencing and bioinformatics.2 atmosphere.RAW264.7 cells preserved in our laboratory at a low passage number were cultured in a T-75 flask  with Dulbecco’s modified Eagle’s medium  containing 1% L-glutamine, 1 mM sodium pyruvate, 10% foetal bovine serum  and 1% penicillin–streptomycin at 37 °C in an 5% COMycobacterium bovis Bacillus Calmette-Guérin (BCG) St. Pasteur 1173P2 strain was frozen and stored in our laboratory. The BCG bacilli were grown in Mycobacterium complete medium  at 37 °C, which was achieved to the logarithmic phase of growth after 10 to 12 days of culture and then aliquoted. A turbidimetric assay was conducted with a spectrophotometer  to measure the optical density (OD) of the bacteria at a wavelength of 600 nm. Once the OD value of the culture medium reached approximately 0.9–1.0, the BCG bacilli were harvested by centrifugation for 10 minutes at 4500 rpm and then resuspended in DMEM without antibiotics as previously described [2 flasks (5 × 106 cells/flask) prior to the day of infection. All the cells were classified into a non-infected group (Group A) and an infected group (Group B), and each group was analysed in triplicate. On the day of infection, the macrophage monolayers were gently washed three times with phosphate buffered saline  at room temperature. The cells in Group B were stimulated with BCG at a multiplicity of infection (MOI) of 10 and incubated at 37 °C in an incubator  with 5% CO2 atmosphere for 4 hours, whereas PBS was added to the cells in Group A as a control. After incubation, the supernatant culture medium was replaced, and the adherent monolayers were tenderly washed with warm (37 °C) PBS  three times to exclude extracellular bacteria [The cells were planted into twelve 75 cmbacteria . Added fThe Cell Culture Media Exosome Purification Kits  were used to extract exosomes from the above-described cell culture medium in accordance with the instructions. Concisely, the required cell culture supernatants were gathered, transferred into a conical tube, and centrifuged  to discard cells and debris, and the cell-free medium was then transferred to a fresh conical tube for the exosome purification. ExoC buffer and Slurry E were added separately to fresh media at different proportions according to the instructions, vortexed for 10 seconds at first and then incubated for 10 minutes at room temperature. The media were remixed and centrifuged for 2 minutes at 2000 rpm. Subsequently, the ExoR buffer (600 μl) were applied to the slurry pellet, and the pellet was incubated for a quarter at room temperature and centrifuged at 500 rpm for 2 minutes. The supernatants were then moved into a fresh Mini Filter Spin column and centrifuged at 6000 rpm for 1 minute. PBS was chosen to suspend the sedimentation and preserved it at − 20 °C. Transmission electron microscopy (TEM)  and nano flow cytometry  were used to characterize the purified exosomes. Total exosomal RNA isolation and extraction were performed using an exosomal RNA isolation kit  according to the instructions. The RNA concentration and purity were detected by Agilent 2100 Bioanalyzer .The construction and sequencing of Small RNA library comply with the standard operating program provided by Illumina. A TruSeq Small RNA Sample Prep Kit  was utilized to prepare the library. After that, an Illumina HiSeq 2500 instrument was chosen to sequence the constructed library. An in-house program, ACGT101-miR  was applied to subject the raw reads and to delete junk sequences, adapter dimers, low complexity reads and duplicates. Finally, 18 ~ 26 nucleotides distinctive sequences were mapped to precursors of specific-species in miRbase 22.0 using the Basic Local Alignment Search Tool (BLAST) to discriminate against known and novel miRNAs derived from 3p and 5p.t test. Based on standardized deep sequencing, the differential expression genes were screened by p ≤ 0.05. Differential miRNA cluster analysis was selected to determine the cluster pattern of miRNA regulation under diverse experimental conditions. According to the statistical similarity of the miRNA expression profiles of the samples, miRNA cluster analysis was applied to intuitively display the distribution of miRNAs in different samples using the log10-transformed normalized values in the heatmap. An advanced volcano map was plotted to manifest the overall distribution and expression levels of these miRNAs.The differential expression of miRNA was analysed by the Student ‘s Prediction of the target genes of differentially expressed miRNAs was accomplished by TargetScan (v5.0) and Miranda (v3.3a). The overlap between the data predicted by the two algorithms was obtained. Targeted genes with a context score less than 50 obtained with the TargetScan algorithm were filtered, and those with a maximum free energy  greater than − 10 obtained with the Miranda algorithm were removed. The intersections between these two software programs were considered the ultimate target genes and their Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) information of these miRNAs was annotated.p value ≤0.05, and the genes satisfying this condition were considered as dominant and endogenous genes. The GO and KEGG functional enrichment analysis of the screened target genes were accomplished by using the OmicStudio tools (https://www.omicstudio.cn/too).The enrichment analysis mainly consisted of two evaluations: GO and KEGG pathway functional annotation. First, count the number of genes corresponding to each function or pathway annotation for all selected miRNAs, and then perform hypergeometric test to determine the number of genes corresponding to different terms in the annotation library. The threshold was defined as https://metascape.org). Based on the membership similarities, those p value less than 0.01, enrichment factor more than 1.5 and a minimum count of 3 terms were gathered and classified into clusters. In addition, a protein–protein interaction (PPI) enrichment analysis was accomplished using the following databases: STRING [The target genes which involved in cell growth and death regulation were selected and used for the subsequent data visualization analysis with Metascape , and the total RNA was extracted from the exosomes. A ReverTra Ace qPCR RT Kit  was used for the cDNA reverse transcription according to the instructions provided by the manufacturer. A stem–loop method was selected for the first-strand cDNA synthesis, and the primer sequences are presented in Table t - test. Statistical significance was assumed at p<0.05.The statistical analysis was performed using GraphPad Prism 8.4 independent sample The supernatants from the culture media from the two groups were collected and used for the exosome isolation. The exosome morphology was evaluated by TEM. NanoFCM was used for the detection of exosome transmembrane proteins (CD9 and CD81) and to determine the particle concentration and size distribution.9 particles/ml, and the particle size was mainly distributed in the 60–80-nm range , and in total, 5576 target genes were effectively enriched.Finally, a number of 5643 target genes were predicted by using TargetScan (v5.0) and miRanda (v3.3a) software. GO and KEGG enrichment analysis of the screened target genes was then performed using the OmicStudio tools  enrichment analysis revealed that 92.88, 71.98, 45.57, 43.33, 43.33, 34.36, 30.28, 27.73, 25.39 and 22.84% of the target genes mainly participated in signal transduction, the G protein-coupled receptor signalling pathway, response to stimulation, the detection of chemical stimulation related to olfactory perception, olfactory perception, the positive regulation of transcription through RNA polymerase II, transcription regulation of DNA template, multicellular biological development, cell differentiation and phosphorylation, respectively. In addition, 18.05% of the target genes also participated in the oxidation–reduction process, protein transport, phosphorylation and ubiquitination, ion transport, the cell cycle and the regulation of apoptosis.As demonstrated by the cellular component (CC) enrichment analysis, 90.91, 63.42 and 58.69% of the target genes were involved in cell membrane composition, cytoplasmic composition, and plasma membrane composition, respectively. In addition, 52.03, 35.28, and 28.85% of the target genes participated in the composition of the nucleus, cytoplasmic cells, and nucleoplasm, respectively.The molecular function (MF) enrichment analysis demonstrated that 65.59, 33.03, 22.53 and 20.25% of the target genes participated in protein binding, metal ion binding, G protein-coupled receptor activity and transferase activity, respectively. In addition, some genes were found to be involved in the combination of nucleotides and ATP and DNA molecules. The results of the GO enrichment analysis are presented in Fig. The results of the KEGG enrichment analysis revealed that the target genes primarily participated in the modulatory control of human diseases, metabolism and biological systems. In addition, a large proportion of genes were classified into the categories of cellular process, environmental information processing and genetic information processing. In this section, the percentage of genes refers to the percentage of significantly enriched genes in the corresponding secondary categories.As shown in Fig. https://metascape.org) was selected to visualize and analyse the biological functions of the target genes enriched in cell growth and death regulation. A total of 183 genes were transformed into their corresponding M. musculus Entrez gene IDs, and related enrichment analyses were then performed. The top 20 clusters and their representative enriched terms were converted into a network layout.Metascape . Their expression tendencies were consistent with the sequencing data. It is indicated that the result of high-throughput sequencing was accurate and reliable.Finally, eight miRNAs including mmu-miR-27-3p, mmu-let-7a-5p, mmu-let-7c-5p, mmu-miR-25-3p, mmu-miR-98-5p, mmu-miR-30a-3p, mmu-miR-194-5p and mmu-miR-5110 were randomly selected from the list of differentially expressed miRNAs, and their relative expression levels in each group were detected and presented in Fig. In the present study, six miRNAs differentially expressed in exosomes derived from RAW264.7 cells infected with BCG were preliminarily screened. The bioinformatics and enrichment analysis demonstrated that these exosomal miRNAs and their target genes were predominantly involved in multiple biological processes and signal pathways related to cellular growth and death.TB remains a fatal threat to global human health and safety and ranks first in terms of mortality rate among all infectious diseases, and no optimal treatment for the effective control of TB infection has been established. Mtb is a typical intracellular pathogen that causes TB infection and mainly infects macrophages, which serve as the initial sites of pathogen survival and replication; and this finding also provides a potential mechanism for controlling the activation of uninfected macrophages mediated by T cells . Once a In contrast, Mycobacterium infection can also alter the host cell exosome content. Our high-throughput sequencing data provided the best evidence. As shown in Fig. Macrophages constitute the front line of defence in innate immunity, and apoptosis plays a critical role in the clearance of intracellular pathogenic bacteria . Howeverp < 0.05) and fit for the subsequent analysis.Thus far, most previous studies have attempted to reveal the complex mechanisms of host-pathogen interactions at the cellular miRNA level, but the detailed roles of miRNAs in TB infection remain poorly understood. Therefore, we explored the possible related mechanisms at the exosomal miRNA level and attempted to unravel the secretion of Mtb during immune evasion. Our study demonstrated that the exosomal miRNAs expression level from the cell culture medium of macrophages between the two groups showed significant differences. Twenty-seven differentially expressed miRNAs were screened from the comparison of the infection and non-infection group, and these included 20 upregulated and 7 downregulated miRNAs, respectively, in the infection group. Among them, mmu-miR-27b-3p, − 93-5p, − 25-3p, − 1198-5p, −let-7c-5p and -let-7a-5p were the top six significantly differentially upregulated miRNAs .The KEGG enrichment analysis demonstrated that the predicted target genes widely participated in the regulation of pathways related to the following categories, including human diseases, metabolism, cellular processes, environmental information processing, genetic information processing and organismal systems. The results of this analysis contains apoptosis, focal adhesion, neuroactive ligand–receptor interaction, the p53 signalling pathway, hepatitis B, EGFR tyrosine kinase inhibitor resistance, microRNAs in cancer, the TNF signalling pathway, endocrine resistance, mismatch repair and the PI3K-Akt signalling pathway , which indicated that the high-throughput sequencing results were relatively accurate.Above all, we found 27 differentially expressed exosomal miRNAs in exosomes derived from BCG infected RAW264.7 cells, their target genes were positively corelated with the regulation of apoptosis. This discovery provides relatively strong evidence revealing the mechanism through which Mycobacteria evade the immune system at the exosomal miRNA level. Furthermore, it also provides an important direction for the subsequent screening of specific miRNAs to investigate the detailed mechanism of host-pathogen interactions during TB infection for our team. Eight miRNAs, namely, mmu-miR-27b-3p, − 25-3p, − 98-5p, −30a-3p, − 194-5p, − 5110, −let-7a-5p and -let-7c-5p, were randomly selected from the list of differentially expressed miRNAs to verify the accuracy of the high-throughput sequencing data by qRT–PCR. The relative expression of mmu-mir-27b-3p, −let-7c-5p, − 25-3p, − 98-5p, −let-7a-5p and -30a-3p in the infection group indicated a consistent trend with the previous sequencing results, but the relative expression levels of the rest two miRNAs were contrary to the results obtained by sequencing, which may be related to the two different methods used for the exosome isolation and exosomal RNA extraction. Overall, the relative expression levels of the miRNAs showed significant differences between the infection and non-infection group (Exosomes are an important area of research related to human diseases and infectious agents that has sparked interest in recent years. Because exosomes have the characteristics of biocarriers and possess information regarding the body’s pathological state with respect to the immune system, they may be used as regulators of the immune response to activate the regulation of the host immune response and infection . In our Mycobacterium Bovis Bacillus Calmette-Guérin infection, and the differentially expressed miRNAs were involved in multiple biological processes and signalling pathways. The top six up-regulated miRNAs and their targeted genes were predominantly correlated with the regulation of apoptosis. However, the mechanisms through which Mycobacteria evades immune surveillance during its infection remain complex. The interplay between pathogens and host cells is an intricately linked event involving multiple factors, such as the Mycobacteria species, the bacteria virulence, the duration of the infection stimulus, even the status of macrophages and other immune cells, which might influence the prognosis and outcomes of TB.It is concluded that Mycobacteria could alter the expression profile of miRNA in exosomes derived from macrophage after


Lysine acetylation is an important regulatory post-translational modification (PTM) that occurs sub-stoichiometrically, often representing less than 1% of the target protein. This makes studying endogenous protein acetylation extremely challenging. Recent reports suggest that several post-translational modifications (PTMs), including lysine acetylation, play a major role in the regulation the programmed cell death-ligand 1 (PD-L1), a clinically important protein target. An enrichment step is necessary to enable identification of the acetylated species by either antibody or mass spectrometry-based detection methods. This report describes a robust lab protocol for the enrichment and detection of endogenous acetylated PD-L1 protein. A recently developed acetyl lysine affinity matrix was utilized to enrich >90% of acetylated PD-L1 species, from a variety of cell lines, spanning a fourteen-fold range of target protein levels. Western blot analysis, using a highly sensitive PD-L1 antibody and optimized transfer times, was used to determine that the endogenous level of acetylated PD-L1 is in the range of 0.02–0.07% of total PD-L1. As validation, we demonstrate that acetylation levels increase to 0.11–0.17% of total PD-L1 after a 4h treatment with the histone deacetylase (HDAC) inhibitor trichostatin A (TSA). The method described here is simple to perform in any lab equipped with tissue culture and western blot equipment. Immune checkpoint therapy targeting PD-L1 protein has shown remarkable results in the treatment of a variety of cancers. However, the response within patient cohorts varies considerably, making it clear that a thorough mechanistic understanding of PD-L1 regulation is lagging the clinical success of this target. It is anticipated that such advances will lead to more efficacious clinical use and novel therapies [Lysine acetylation is a key regulator of protein function and is involved in cell processes such as transcription, metabolism, and signal transduction . AcetylaHere we present a modified protocol of Horita et al. . The metThis technique compliments the alternative IP approach utilizing a PD-L1 antibody as the IP reagent and an anti-acetyl lysine antibody as the detection reagent. However, because the protocol described here enables the detection of both total and acetylated PD-L1 on the same blot, this method has the advantage of allowing an estimate of the percent of PD-L1 that is acetylated, an important parameter for mechanistic interpretation.Unlike quantitative mass spectrometry, this method does not have the potential to identify and quantitate specific endogenous acetylation sites. The specialized equipment and high level of expertise that quantitative mass spectrometry of sub-stoichiometric species demands is out of reach for most laboratories and is technically demanding even for specialist labs; currently the only reported quantitative mass spectrometry of a PD-L1 PTM is the abundant modification of N-glycosylation . The devhttps://dx.doi.org/10.17504/protocols.io.bxgcpjsw.The protocol described in this article is published on protocols.io, The protocol described can be used to estimate the percent of PD-L1 that is acetylated in any given cell lysate. The enrichment step requires a 48h incubation period with 70–80% of acetylated PD-L1captured over 24h and >90% after 48h . ImportaThe assay was used to examine cell lines spanning a 14-fold range of PD-L1 protein levels , Fig 2A.Re-probing the western blot with a pan anti-acetyl lysine antibody  allows vS1 File(PDF)Click here for additional data file.


The 1860 bp SBP sequence was analyzed using Plant Care and PLACE databases to find cis-acting elements, which resulted in a finding of 22 cis-acting elements required for seed expression. In addition, we have discovered cis- acting elements that are indirectly involved in triacylglycerol synthesis . The seed specificity of SBP was analyzed by generating a stable transgenic tobacco plant harboring β-glucuronidase (GUS) reporter gene under the control of the SBP promoter. Histochemical analysis of these transgenic tobacco plants indicated decreasing GUS activity in the leaves during the vegetative stage. However, the mature seeds of transgenic plants showed GUS activity. Moreover, the SBP promoter function in the seed oil content was evaluated by the expression of DGAT1. The expression analysis of DGAT1 in SBP-DGAT1 transgenic tobacco seeds using quantitative real-time PCR revealed a 7.8-fold increase in DGAT1 than in non-transgenic plants. Moreover, oil content increased up to 2.19 times more than in non-transgenic plants. And the oil content of the SBP-DGAT1 transgenic tobacco leaves did not change compared to the control plant. Therefore, we suggested that the SBP promoter could be used as a seed-specific promoter for targeted expression of desired genes in the metabolite engineering of oilseed crops.Seed-specific expression using appropriate promoters is a recommended strategy for the efficiently producing valuable metabolites in transgenic plants. In the present study, we investigated the sequence of sucrose binding protein (SBP) as a seed-specific promoter to find the  Spatiotemporal, constitutive, and inducible promoters are three types based on their expression patterns. Spatiotemporal promoters, used for genetic engineering, lead to specific expression in targeted tissues or organs . β‐congln cotton , γ-zein n cotton , Glutenin cotton , and Vvβin Vitis  were repCis-acting elements, are located upstream of the start coding site, regulate gene expression at the promoter level [cis-acting elements could enhance gene expression in a tissue-specific and temporally regulated manner during embryo development in plants [er level  and leader level –11. It hn plants .The required carbon for fatty acids (FA) synthesis can be prepared via two routes: 1- glycolytic reactions, and 2- ribulose-1,5-bisphosphate carboxylase. Pyruvate and NADPH produced in light reactions, increase the carbon required to synthesis of fatty acids . A commoAnother way is using the effect of sucrose carriers’ on plant development and carbon allocation controlling . Therefoi.e., VfSUT1 and VfSTP1, respectively) as sucrose carriers, control carbohydrate availability during seed development of fava bean [Brassica. napus L., unloaded sucrose from the phloem was imported to the glycolytic route. Afterward, it was converted to intermediates like hexose-phosphates, phosphoenolpyruvate, and pyruvate that was transferred subsequently to plastid to be used in fatty acid synthesis [Sucrose and hexose transporters (ava bean . It was ynthesis .SBP genes (Y11207 and VFA292221) were isolated from pea and Vicia faba, respectively. Conserved regions between the SBP gene and vicilin-like protein have been reported. Vicilin-like protein contributes to the storage proteins of the seeds [Sucrose binding proteins (SBPs) were reported in the plasma membrane of various tissues in the ripe vegetables of soybean, play an essential role in the quality and indirectly yield . SBP wasde novo TAG production from Glycerol-3-Phosphate (G3P) and acyl CoA is done through the Kennedy pathway [The  pathway , 23. Thi pathway .LPAAT [GPAT [AtDGAT1 [DGAT genes in DGAT gene families, DGAT1 plays a more critical role in TAG biosynthesis in Soybean and Arabidopsis than others [LPAAT , GPAT [2AT [GPAT , and AtD[AtDGAT1 , 26 are n others , 28.GmDGAT1A on TAG production in soybean seeds has been reported [GmDGAT1A on changes in the oils and fatty acid levels in plants is well studied [It was shown that DGAT1 is a necessary enzyme in the biosynthesis of seed TAG and seed oil accumulation consequently . The effreported . The con studied , 30–32.Brassica carinata increased the amount of docosadienoic acid (DDA) and docosatrienoic acid (DTA) in the seeds by 30% in total fatty acid [DGAT1 and GPD1 genes using two seed-specific promoters, i.e., oleosin and glycinin led to an increase of up to 13% in seed oil content in Camelina sativa [Recently it was shown that seed-specific promotors led to improve oil content . Moreovetty acid . In addia sativa . Therefocis-elements and seed-specific motif sequences in the SBP sequence promoter. Regarding the fact that a desirable seed-specific promoter should be active in seeds with no effect on other tissues, and due to the importance of SBP in the production of FA and TAG; the specificity of the SBP during vegetative and reproductive stages, and its effect on DGAT1 expression on the TAG pathway and oil content in transgenic tobacco plants was measured.The present study aim, was to identify the This could introduce SBP as a promoter to overexpression of enzymes to further improve seed oil content in commercial oilseed crops.cis-elements in the SBP sequence were searched and recognized in two online tools: PLANTCARE [Initially, the SBP sequence was retrieved in PlantPromDB  to find LANTCARE  and PLACLANTCARE . The desDGAT1 sequence (accession number KU744408.1) was used to construct the pSBP-DGAT1 following codon optimization based on the safflower sequence. SBP sequence with accession number AJ277287 from Vicia faba was used as a promoter sequence. Then, the constructs were designed by DNASTAR_lasergene software [AvrII and XhoI and cloned into the pGH-SBP vector and confirmed by enzyme digestion. Then this vector was digested with Hind III and sub-cloned into pBIN19, and the construct was named pSBP-DGAT1  (1 mg/1), containing kanamycin sulfate (100 mg/1) and cefotaxime (250 mg/1). Afterward, seedlings were transferred into pots and grown in greenhouse conditions. Tobacco plants transformed with the pBI121 binary vector were used as a control in the experiments. Seeds of transgenic lines in T0 generation were selected in selection media containing 150 mg/l kanamycin sulfate. These plants were subsequently analyzed by PCR. The T1 PCR positive lines were selected and brought to T2 generation. The last step was repeated on T2 generation lines to gain homozygote seeds.The agrobacterium-mediated method was used to transform tobacco plants nstructs . After tDNA was extracted using the CTAB 2% method from three generations of leaves of putative transgenic plants . PrimersThe youngest leaf , sepal, stamen, petal (T1 generations), and seeds  were sampled at different stages of the vegetative and reproductive phases.These tissues in different stages and generations of SBP-GUS, 35S-GUS, and non-transgenic plants, were prepared and assayed as described by Kosugi method. . TissuesSeeds and leaves of one SBP-DGAT1 event and non-transgenic lines were prepared at the final phase of seed development. They were instantly placed in the liquid nitrogen and stored at—80°C. In the next step, the frozen tissue was ground under liquid nitrogen using a grinder . Isolation of total RNA from seeds and leaves was carried out using Trizol reagent genomic. DNAs were removed via a DNase І treatment. The quality of isolated RNA was determined by electrophoresis on the agarose gel. The quantity of total RNA was finding out by the Nano Photometer apparatus (IMPLEN).https://www.ncbi.nlm.nih.gov). The qRT-PCR reaction was made with 5μl of diluted cDNA, 10 μl of 2X PCR Master Mix, and 1 μl of each primer (10 pmol). The final volume reached 20 μl with double distilled water. The PCR program consisted of several steps: 5 min at 94˚C, 40 cycles of 10 sec at 95 ˚C, 60 sec at 49 ˚C, 10 sec at 72 ˚C, and a final step of 30 sec at 72 ˚C. A melting curve analysis including 81 cycles at 55–95 ˚C with 0.5˚C increases in each cycle was performed to evaluate the primer specificity. The real-time PCR was done using the Roche Real-time system. Relative expression ratios were calculated through the comparative ΔΔCT method by REST software for relative gene quantification, according to equation 1. A housekeeping gene  was applied as a reference gene with equal transcripts in all stages and tissues.Revert Aid First Strand cDNA Synthesis Kit (Fermentase) was utilized for synthesizing cDNA. Quantitative Real-Time PCR (qPCR) experiments were implemented and replicated three times using BIO FACT real-time master mix. Primers were designed by Primer 3 online software  and syntFifteen’s grams of seed and leaf from replications of three SBP-DGAT1 events, were ground, then moved into pre-weighed Whatman bags (Weight A) and sealed. These samples were oven-dried until reaching constant weight (Weight B). After that, the bagged sample was transferred into a Soxhlet tube and extracted with 120 ml petroleum ether for 24 h. The solvent was evaporated by heat, and after condensation was poured on the sample by the upper part of the device (glass refrigerant). When the Soxhlet tank was complete, the solvent and liquid extracted (oil) were returned to the balloon through a thin glass siphon. This cycle was repeated for 4 hours until almost all oil was transferred to the solvent. After the extraction, the bagged sample was dried to evaporate the remaining petroleum ether (Weight C). The oil content (%) was determined by (B—C)/(B—A)* 100%  formula.Gas chromatography (GC) was used to determine the Fatty acid composition from replicates of three SBP-DGAT1 events. For this purpose, TAG is converted to methyl ester based on the INSO 14880 standard method entitled “Oilseeds—Oil extraction and preparation of triglyceride fatty acid methyl esters for analysis by GC” (rapid method). Twenty ml of iso-octane was added to 0.1 gr of the sample. Then, 0.1 ml of 2 M potassium hydroxide methanol solution was added to the test. The lid was placed, and the sample was shaken vigorously for 1 minute. The solution was allowed to stand for 2 minutes. Subsequently, 2 ml of sodium chloride solution was added, and the mixture was shaken again. The iso-octane layer was dried over sodium hydrogen sulfate and injected into the GC  temperature: 220°C. Injection volume: 0.4 μL. Colum oven: 170°C (5 min Hold) to 190°C Rate: 0.5°C/min. Column: DB WAX, 60 m, 0.25 mm (ID), film thickness: 0.25 μm) .Mature seeds were harvested from non-transgenic (WT), and tobacco plants were grown under the same conditions. Three hundred seeds from non-transgenic and SBP-DGAT1.H1, F, and C2 tobacco plants in three replicates were oven-dried at 37°C for 24 h to ensure all the seed moisture content of samples was equal. The seeds were weighed by analytical balance. Mature seeds were photographed with a stereoscopic microscope , and the seed size was analyzed by Image J 1. X software.One-way ANOVA was used to compare six transgenic and non-transgenic plants for measurements of seed and leaves percentage oil content, FA composition, seed size, seed weight, and fold-change in gene expression. The values represent at least three biological replicates. A p-value < 0.01 was considered as significant. The individual lines were compared again by non-transgenic by LSD test as indicated in the fig legends using SAS (version 6.4) for the data with significant differences.cis-acting elements, including: i) general transcription factors; ii) cis-acting in the regulatory element expressed in the seeds; iii) cis-acting in regulatory element related to abscisic acid (ABA); iv) cis-acting in the regulatory element in the TAG pathway indirectly, and v) other cis-acting regulatory elements. The cis-acting regulatory elements related to seed expression and tissue-specific expression are categorized in , which indicates no data about SBP has been reported yet. However, database searching at PLACE revealed that SBP contains 37 diverse rized in .cis-elements contribute to seed-specific expression or the TAG pathway, indirectly. GATABOX interacts with HvMYBS3 in yeast three-hybrid assays, and HvMYBS3 enhances the expression of the developing endosperm-specific gene in barley seeds [We have found 22 sequences that are expressed in the seeds directly. However, some ey seeds . AccordiDOFCOREZM, as a member of DOF proteins by AAAG sequence, regulates the expression of genes that correlate with carbon metabolism in maize. We found this motif in SBP with 12 repeats in the + strand and 19 repeats in the–strand, which indicates the importance of this motif in carbon metabolisms .Catharathus. roseus strictosidine synthase gene promoter controls CACGTGMOTIF [RbcS promoters [CACGTG MOTIF, or G-box was found in the SBP sequence of six bp position in both strands of our studies which was reported seed-specific expression in GTGMOTIF . Moreoveromoters .cis-element searching on Napin sequence as a strong seed-specific promoter, we observed eight seed-specific cis-elements identical to those in SBP include: MYCCONSENSUSAT, MYB1AT, SEF4MOTIFGM7S, DPBFCOREDCDC3, MYB2CONSENSUSAT, NAPINMOTIFBN, RYREPEATBNNAPA, and EBOXBNNAPA, which have been explained previously.Besides, by cis-elements in SBP were reported in other plants as seed-specific cis-regulatory elements.Furthermore, the AACA motif , GCN4 mocis-elements in response to environmental and hormone signals like ethylene-responsive element, light-responsive cis-acting element, anaerobic induction elements, defense, stress responsiveness elements, and salicylic acid responsiveness element.Moreover, we demonstrated other sbp and nptII genes in the SBP-GUS putative transgenic plants and nptII and DGAT1 genes in SBP-DGAT1 putative transgenic plants. Moreover, the absence of remaining bacteria was confirmed when amplification with vir specific primers was not detected in the DNA of transgenic plants  in SBP-GUS transgenic plants . MoreoveTransgenic T1 generation seeds (SBP-GUS and 35S-GUS) were selected on media containing kanamycin for achieving the T2 generation lines. T2 generation of transgenic SBP-GUS, 35S-GUS, and wild-type plants, were investigated in three developmental stages  using GUS-assay analysis . As expeSBP gene in other plant tissues. Bahry and Zimmer (2016) reported a higher level of SBP expression in the initiation stage of seed coat development of soybean [Various reports have been presented on the different expressions of the  soybean . Moreove soybean . The exp soybean . DespiteVfSBPL expression in yeast and transgenic potato plants did not affect in sucrose transport and carbohydrate status, respectively [VfSBPL was expressed in seeds while GmSBP1 transcript levels were confirmed in young sink leaves [While soybean SBP accelerates sucrose uptake, ectively . Interesk leaves .The present functional analysis of the SBP promoter confirmed the preliminary results of the sequence analysis on the specific activity of the SBP promoter in the plant seeds.DGAT gene expression under the control of seed-specific promoters [DGAT gene expression of leaves.DGAT1 expression was measured by real-time PCR. The results showed a higher gene expression level in seeds of transgenic plants in T3 generation by 7.8-folds more than in control plants . These rromoters , 60. AlsThe seed and leaf oil content (based on dry weight) of independent transgenic lines (T3 generation) and SBP-DGAT1 transgenic lines were analyzed as described in the material and method section. The average oil content in non-transgenic tobacco plants was 31.43%. However, it was 68.99% for SBP-DGAT1 transgenic lines, which showed 2.19 times more than non-transgenic lines . As showDGAT1 gene under the control of the Oleosin promoter in Arabidopsis led to an increase in oil content up to 8.3% compared to the wild-type plants [DGAT1 gene under the GmUbi3 promoter led to a reduction in oil content in soybean to 8.3% [AtDGAT1 expression under the control of Napin, as a seed-specific promotor, showed an 11–29% increase in oil content in transgenic Arabidopsis plants [DGAT1 allele, PH09B, in the maize by controlling of an oleosin promoter resulted in an increase in kernel oil of about 1% in transgenic maize plants [AtDGAT1 in B. napus, under the control of the Napin promoter, increased the seed oil content by 2.5% to 7% [Transferring the e plants . The sim to 8.3% . Moreoves plants . The expe plants . Moreove5% to 7% .DGAT1 gene, driven by the SBP promoter, cause a significant increase in the content of Palmitic acid, Palmitoleic acid, Margaric acid, Oleic acid, Vaccenic acid by 12.1%, 33.9%, 10.79%, 10.16%, and 5.7% respectively. However, Stearic acid, Linoleic acid, Linolenic acid, and Arachidic acid contents decreased to 12.39%, 1.83%, 28.6% and, 38.1%, respectively . Nine principal fatty acids were Palmitic acid (16:0), Palmitoleic acid (16:1), Margaric acid (17), Stearic acid (18:0), Oleic acid (18:1.9), Vaccenic acid (18:1.11), Linoleic acid (18:2), Linolenic acid (18:3), and Arachidic acid (20:0). According to GC results, the expression of the ectively .monounsaturated fatty acid vital for fighting pathogens, transporting minerals, and responding to hormones. Oleic acid also serves as the most important energy source for our cells, and it’s used for the production and biosynthesis of many crucial metabolites [The fatty acid profiles of seed oils in oilseed crops are characterized by three fatty acids: Palmitic acid, stearic acid, Oleic acid, and Linoleic acid . Oleic aabolites . It was abolites –67. Moreabolites , 68. AccDGAT1 gene [Arabidopsis transgenic plants by DGAT1 showed a 3.5%–10% increase in seed weight and total seed yield in transgenic lines [DGAT1 soybean transgenic lines showed a significant increase in seed weight than the control plants [Transgenic seeds showed no significant changes in size compared to non-transgenic seeds . Our finAT1 gene , 70. A sl plants .cis-elements. SBP-GUS construct was transferred to the tobacco plant as a model plant. The activity of the SBP promoter in different stages, from germination to the seedling stage was investigated. After introducing DGAT, which is regulated by SBP promoter, the oil content and composition of FA were evaluated.In the current study, we proposed SBP as a seed-specific promoter to prompt the oil content in oilseed crops. The SBP promoter was examined in the presence of seed-specific motifs and DGAT gene in the seeds of transgenic plants was 7.8-fold higher than of control plants. On the other hand, the expression of this gene in the leaves of transgenic plants did not show any change compared to control plants. These results also indicate more effect of the promoter on the seed than other tissues. Based on our results, SBP as a seed-specific promoter can be exploited as a novel promoter for over-expression of essential genes in oilseed crops in favor to increase oil and oleic acid content, as essential seed traits for getting better the quality of oil which have various usage in food, medicinal and industrial.As a result, the maximum activity of the SBP promoter could probably be observed in the seed stage of oil plants, which is desirable for seed-specific expression of oil metabolism-dependent genes. The expression of the DGAT1 expression and accumulation of seed oil content is significant. Also, the oil content in the leaves did not show any significant changes. In addition, we have found a noticeable increase in Oleic acid and decreasing in Linolenic acid contents in the transgenic lines. Additional studies can help to understand the function of this promoter better. And transferring the genes related to TAG pathway under the control of SBP promoter and analysis of changes in the oil content in various tissues in tobacco and oily plants are suggested to understand the function of this promoter. Reporting any firm conclusions requires other well-designed research and experiments. This was an attempt to open the way for future investigations.In conclusion, we revealed that the effect of SBP on S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Raw images(PDF)Click here for additional data file.


Deciphering the population structure of SARS-CoV-2 is critical to inform public health management and reduce the risk of future dissemination. With the continuous accruing of SARS-CoV-2 genomes worldwide, discovering an effective way to group these genomes is critical for organizing the landscape of the population structure of the virus. Taking advantage of recently published state-of-the-art machine learning algorithms, we used an unsupervised deep learning clustering algorithm to group a total of 16,873 SARS-CoV-2 genomes. Using single nucleotide polymorphisms as input features, we identified six major subtypes of SARS-CoV-2. The proportions of the clusters across the continents revealed distinct geographical distributions. Comprehensive analysis indicated that both genetic factors and human migration factors shaped the specific geographical distribution of the population structure. This study provides a different approach using clustering methods to study the population structure of a never-seen-before and fast-growing species such as SARS-CoV-2. Moreover, clustering techniques can be used for further studies of local population structures of the proliferating virus. The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [As a newly emerging pandemic virus, exploring the genetic diversity, evolutionary trajectory and possible routes of transmission of SARS-CoV-2 from its natural reservoir to humans is crucial for supporting clinical studies. For that reason, studies have implemented phylogenetic trees to investigate the evolutionary trajectory of SARS-CoV-2 and its strain diversification ,4,5. A pWith the development of machine learning algorithms, machine learning-based approaches have played a critical role in phylogenetic analysis. Compared with other methods, machine learning-based methods can find a better balance between accuracy and running time . To our In this study, to elucidate the genetic structure and evolution of early SARS-CoV-2, we downloaded 16,873 genomes from the published database, and used a clustering model based on the recently published state-of-the-art deep embedding clustering (DEC) method  to clusthttps://db.cngb.org/gisaid/, accessed on 15 May 2020). Only the strains marked as “high coverage” were maintained in our study. In terms of GISAID, the definition of “high coverage” was strains with <1% Ns and <0.05% unique amino acid mutations (not seen in other sequences in databases), and no insertion/deletion unless verified by the submitter. Moreover, non-human host strains and assemblies of total genome length less than 29,000 bps strains were removed. A total of 16,873 strains passed the filtration. The Accession IDs with demographic information for the strains are listed in The genomes of SARS-CoV-2 uploaded before 15 May 2020 were downloaded from GISAID  of a given strain can be expressed as:A phylogenetic tree was generated using all 16,873 strains. We employed FastTree 2  to recons” was detected in the strain “i”, the cell with the coordinate  was marked as “1”, whereas no mutation was marked as “0”.We achieved a total of 7970 unique substitutions across 16,873 strains through mutation calling. Herein, we used the aggregated substitution profiles to train our unsupervised clustering model. The input of the clustering model was a matrix with dimensions 16,873 × 7970, where each row represented a strain, and each column represented a unique substitution. If a substitution “We implemented a clustering model based on the recently published DEC model  to iterai to cluster j. The P by raising each Based on the equation, the distance on (BIC)  curves. on (BIC) . Moreoveon (BIC) ,27,28. Hd) to measure the pairwise genetic distance between two strains  based on their nucleotide substitutions. Thus, the pairwise genetic distance is the number of nucleotide positions in which the two strains are different. For a cluster (A), N(A) denotes the number of strains of the cluster, and the mean intra-cluster pairwise genetic distance  is a measure of diversity that considers the number of entities as well as their abundance. The index measures the probability that two randomly selected individuals are the same. The formula to calculate the value of the index is:sim ranges between 0 and 1. With this index, 1 represents infinite diversity and 0 denotes no diversity.Simpson’s Diversity Index  and synonymous (dS) substitution rates on a per-site basis to infer pervasive selection. Fast Unconstrained Bayesian AppRoximation (FUBAR) was applied to detect overall sites under positive selection. The positively selected sites were identified using a probability larger than 0.95 using the FUBAR method.X and Y, the score S(X|Y) represents the proportion of strains that accumulated X among the strains that accumulated mutation Y. S(X|Y) and S(Y|X) can be calculated using the following functions:X. The pairwise mutation dependency score displays the correlation and the timescale relationship of the two mutations. The value of S(X|Y) and S(Y|X) ranges between 0 and 1. With this index, S(X|Y) = 1 with S(Y|X) < 1 represents that mutation Y occurs after mutation X. In contrast, S(X|Y) = 1 with S(Y|X) = 1 represents that the two mutations occur simultaneously and are genetically linked. Statistical analyses and data presentations were generated using Python 3.7.6.Pairwise mutation dependency scores can measure the order in which genetic mutations are acquired within a cluster. For two selected mutations For each country with SARS-CoV-2 data available, clustering proportions were calculated and plotted on the world map using the tool Tableau Desktop 2020.2. The T-distributed Stochastic Neighbor Embedding (t-SNE) plot was generated using the aggregated substitution profiles for the 16,873 strains. We used the sklearn.manifold.TSNE package in Python for t-SNE training and the seaborn package in Python for visualization. The other figures were plotted using the ggplot2 in R 4.0.1, the seaborn package in Python 3.7.6 and GraphPad Prism 8.0.2. Statistical analyses, and the clustering models were implemented in Python 3.7.6.We downloaded the whole genome sequencing of SARS-CoV-2 from GISAID, aligned the sequences, and called mutations. Across the 16,873 strains , we identified 7970 substitutions , with 6.99 mutation counts per strain . In termThere were 8706 unique strains within the entire SARS-CoV-2 population; thus, grouping these strains into multiple major subtypes was necessary to informatively formulate their population structure. Making use of the machine learning (ML) algorithms, we applied unsupervised ML models to cluster SARS-CoV-2 strains using their substitution profiles, as SARS-CoV-2 exhibited limited substitutions per strain as well as little ongoing horizontal gene exchange .Our initial work  used an We investigated the distributions of clustering results across continents and found that the clusters diverged in their geographical distributions , Table 1It is noted that approximately 85% of the strains were collected from North America and Europe . Thus, dThe different geographical distributions for the six clusters could be due to intrinsic genetic factors, extrinsic factors such as the migration of humans, or both. Hence, we next aimed to explore the genomic characteristics of these clusters, as well as the transmission and human migration of the virus across the globe.p-value < 0.001, Wilcoxon rank-sum test) than those in other clusters. In contrast, the average mutation rate in cluster F was significantly higher  than those in other clusters. The Simpson’s diversity indexes for the six clusters were 0.7616, 0.7608, 0.8398, 0.8466, 0.8082 and 0.8502, respectively. Both the average mutation rate and Simpson’s index were highest in cluster F, suggesting that the diversity of cluster F was higher than the other clusters. The nucleotide diversity per site for the six clusters was 0.0196%, 0.0222%, 0.0171%, 0.0256%, 0.0131%, and 0.0132%. The high mutation rates but low nucleotide diversity in cluster E and cluster F suggest that these two clusters may have more fixed mutations than the other clusters. The nucleotide diversity values for each gene across all clusters are displayed in If the different geographical distributions for the six clusters were due to intrinsic genetic factors, there would be high genetic variance between the clusters. The average mutation counts for the six clusters were 6.38, 3.49, 6.57, 7.09, 7.89, and 8.96 , respectp-values < 0.05  of them achieved s < 0.05 . We founs < 0.05 . Clusterp-values (We selected the 2% (42/2094) substitutions that achieved the lowest p-values  and analr2) of the 42 substitutions. D′ is affected solely by recombination and not by differences in allele frequencies between sites, and r2 is also affected by differences in allele frequencies at the two sites. In the heatmap of D’ and r2 (Previous studies have reported that recombination is common in coronavirus ,32,33. G’ and r2 , no obviSelection usually affects the distribution of the mutations in the population. Purifying selection tends to remove amino acid-altering mutations, while positive selection tends to increase the frequency of the mutations. Considering the rapidly proliferating pattern of SARS-CoV-2 that strengthened the power of drift relative to the power of purifying selection ,36,37, wRegardless of genetic factors, the travel of humans can also lead to unique geographical distributions in today’s highly globalized world. By analyzing the frequencies of the extracted 42 mutations in each cluster A and theDeciphering the genetic structure and subtypes of SARS-CoV-2 is critical for reducing the risk of future dissemination and assessing efficacy of antibodies on different strains . In thisOne limitation of our study is the sampling bias of SARS-CoV-2 collections. Indeed, approximately 85% of the strains were from North America and Europe . In partspike protein domains was reported to show significant variation in cytopathic effects and viral load, and substantially change the pathogenicity of SARS-CoV-2 [Despite these limitations, our discovery of high genetic diversity in early SARS-CoV-2 is consistent with other published studies . In addiRS-CoV-2 . This muRS-CoV-2 . In addiRS-CoV-2  used mutIn summary, our current study, as well as previously published unsupervised clustering-based SARS-CoV-2 analyses ,52, haveThe SARS-CoV-2 virus has been spreading rapidly and across the globe since first being reported in December 2019. To understand the evolutionary trajectory of the coronavirus, phylogenetic analysis is needed to study the population structure of SARS-CoV-2. As sequencing data worldwide is accruing rapidly, grouping them into clusters helps to organize the landscape of population structures. To effectively group these data, we utilized clustering models to partition the viral sequences into clusters. The partition of the viral sequences revealed six major clusters, and these clusters differed in their geographical distributions. Through multiple approaches, we found that the unique geographical distributions across the clusters were influenced by both intrinsic genetic factors and the migration of humans. Identifying the mutations that are strongly associated with specific clusters has potential implications for the diagnosis and pathogenesis of COVID-19. In addition, our application of clustering techniques has proven to be a valuable method for studying the structure of new and unknown populations.


The optimal interval before receiving SARS-COV-2 vaccination for patients who have received anti-CD 20 monoclonal antibodies remains unclear. We considered original studies up to 29 October 2022 and conducted searches in Embase,Medrxiv, PubMed, and SSRN. We excluded search results that did not match our research question’s subject. Human immune response outcomes were analysed inpatients who had previously received anti-CD20 antibody therapy. We analyzed the collected results using sensitivity curves and forest plots. Twenty-eight studies with a total of 1455 subjects receiving anti-CD20 monoclonal antibodies were included in the present analysis. The humoral immune response rates to the time between the last anti-CD20 treatment and vaccination for 3–6 months, 6 months,6–9 months, and 9–12 months were 0.23 (95% CI 0.14 to 0.36), 0.36 (95% CI 0.19 to 0.58), 0.49 (95% CI 0.35 to 0.64) and 0.64 (95% CI 0.48 to 0.77),respectively. The humoral immune response rates were.16 (95% CI 0.03 to 0.57) when B cell was 0/ul, and 0.49 (95% CI 0.38 to 0.61)when B cells were more than 5/ul. The humoral immune response rate for multiple sclerosis was 0.39 (95% CI 0.22 to 0.60) and 0.48 (95% CI 0.29 to 0.68) for B-cell non-Hodgkin lymphoma. The area underneath the curve(AUC) was 0.69 with a cut-off value of 5.5 months. The present results suggested that the optimal interval for SARS-COV-2 vaccination after the final dose of anti-CD20 monoclonal antibody was 5.5 months. According to the World Health Organization, the COVID-19 pandemic, which began at the beginning of 2019, will cause 6.5 million fatalities and 624 million confirmed cases worldwide by 23 October 2022. We are still fighting against it, and there are still many unknowns. Fortunately, we have developed the corresponding vaccine, and with the SARS-CoV-2 vaccine’s broad use in numerous nations, it has played a preventive role. However, for some special populations, the patients receiving anti-CD20 treatment, the vaccination’s impact on their humoral and cellular immunity is still unknown.The response to immunization in patients receiving active anti-CD20 medication is reported to be modest and close to 0%, but it appears to gradually improve over time . RegardlTherefore, due to the lack of studies on the cellular and humoral responses of anti-CD20-treated patients, our present study revolves around the analysis of anti-CD20-treated patients receiving the vaccine and gives a higher level of evidence-based medical evidence on whether 6 months is the cut-off point for anti-CD20 treated patients waiting for vaccination.We carried out a systematic review and meta-analysis of preprints and peer-reviewed articles that were accessible online, and we presented our findings in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses.We saw as possibly eligible for inclusion any original research papers that examined the serological and/or cell-mediated reactions to SARS-CoV-2 vaccination in patients receiving anti-CD20 treatment. Unspecified periods between vaccination and blood sampling, unspecified methodology for detecting antibody-mediated or cell-mediated immunity (specification of manufacturers and detection kits mandatory), lower or equal to the three investigated participants, and missing numbers of positive versus negative humoral or cell-mediated immunity were among the prespecified exclusion criteria. Additionally, any search results that did not pertain to the subject of our study question were removed, as well as review and guideline papers.Online searches were performed using title/abstract without regard to language using PubMed (up to 29 October 2022), Embase (up to 29 October 2022), preprint services medrxiv, SSRN, and SSRN-Lancet (1 January 2020–29 October 2022).A PubMed title/abstract search for “rituximab OR anti-cd20 AND vaccination AND covid” was conducted. Embase’s title/abstract section was searched for “rituximab OR anti-cd20 AND vaccination AND covid.” Medrxiv was searched for “Rituximab AND Covid AND Vaccine.” Furthermore, the term “anti-CD20 AND covid AND vaccination” was researched. A third search was carried out using the keyword “anti-CD20 AND covid AND vaccination.” SSRN was searched for “Rituximab AND Covid AND Vaccine.” Another search was performed with the phrase “anti-CD20 AND covid AND vaccination.” The phrase “rituximab AND covid AND vaccination” was found in SSRN Preprints by The Lancet. Another search was conducted using the term “anti-CD20 AND covid AND vaccination.”We followed the Cochrane recommendations when we carried out the study selection process. In addition to two writers (KL and GX) individually evaluating all search results from the EMBASE database and preprint sites, two authors (KL and JL) independently evaluated all search results from the PubMed database. When there were disagreements over the choices, a third author  was consulted. Each of the three authors went over the inclusion and exclusion criteria again, and they then discussed and double-checked their decisions. In every instance, disagreements might be conclusively settled by the unanimous consent of all authors. Due to ongoing conflicts, we did not need to use the predetermined form of majority decisions. We did not use any automated tools.Each reviewer carefully copied and independently downloaded the tabular and text data of study population subsets having a history of anti-CD20 treatment. In some circumstances, image analysis was used to extract data from graphical figures. We did not use any automated tools.Along with the previously mentioned inclusion and exclusion criteria, we gleaned the following data from the studies we searched.A percentage of patients who received anti-CD20 therapy had no prior COVID-19 disease history, finished the SARS-CoV-2 immunization series, and had positive serological results.Primary outcome data are broken down by the amount of time since the previous anti-CD20 therapy , B cell depletion counts , the dose of injected anti-CD20 drugs and disease types of the study population.Research design, cell-mediated immune (CMI) response measurement technique, detection kit manufacturers, and corresponding cut-off values for test positive, study title, digital object identifier, and PubMed identifier are all required for repeated duplicate checks. We obtained these data from the manufacturer’s websites in cases where cut-off values of a manufacturer’s kit for antibody or CMI response testing were not mentioned in the procedures section.Using the Newcastle- Ottawa Scale for evaluating the quality of non-randomized studies in meta-analyses by Wells et al, we manually evaluated the risk of bias in the included studies. For each study, three researchers  independently assigned a range of quality criteria . Results were summarized by a fourth researcher (JL) using a predetermined mode of majority decision. It was anticipated that at least 4 weeks after the second immunization was finished was the cut-off for an ideal follow-up time.The number and percentage of respondents were used for the synthesis and presentation of results for humoral immunity outcomes.2 metric was used to quantify statistical heterogeneity. The Wilson score with 95% CI for each study is shown. We carried out the previously mentioned prespecified subgroup analysis to investigate potential reasons for study heterogeneity. Revman 5.4.1 performed quantitative analysis and produced graphical displays. The results are converted by the formula: P=OR/(1+OR). No sensitivity analyses were performed. ROC curves are plotted using Graphpad Prism. ROC curve data collection using Microsoft Excel, Jorden index calculation done through Microsoft Excel, and determination of cut-off values.Using Microsoft Excel to tabulate the research and compare them to a list of exclusion criteria, a preliminary synthesis was created. In the studies that were included, there were no missing data. Using the Der Simonian and Laird approach, we conducted a random-effects meta-analysis of proportions, stabilizing the variances by computing pooled estimates using the Freeman-Tukey Double Arcsine Transformation. The inverse-variance fixed-effect model’s IA funnel plot and a regression test for funnel plot asymmetry were used to evaluate the effects of small studies.No processes were used to evaluate the body of evidence’s credibility.Supplementary Table 4 reveals the findings of the risk of bias analysis for each of the listed research. Applying the NOS, eight of the nine quality rating criteria could be satisfied . The 28 included studies have a low to moderate risk of bias ratings.The Methods section provides specifics on the proportion calculations for meta-analysis utilizing a random-effects model computation of the effect size. The log [odds ratio] and Standard Error (SE) of each study are first shown separately. The penultimate column, with a 95% confidence interval, displays the percentage weight of the particular study. The final column displays the combined odds ratio estimates.2 of 88% , the forest plots showed that the humoral immune response rates corresponded to 23%, 36%, 49%, and 64% for 3–6 months, 6 months, 6–9 months, and 9–12 months, respectively, the overall humoral immune response rate was 38% . StudiesFor the question of how long it has been since the last anti-CD20 treatment, ROC curves were created . From thWe explored whether current counts of B cell depletion are related to worse seroconversion rates, similar to the time window since the last anti-CD20 medication. Patients with low levels of B cells had fewer responders, The humoral immune response rate was 16% when B cells were 0/ul, and 49% when B cells were 0-5/ul, and >5/ul , which means that the optimal value for the interval between the most recent anti-CD20 treatment and immunization in individuals who have received anti-CD20 treatment is 5.5 months. This is consistent with the value taken for the time interval in Firinu et al , and SchIn Firinu’s study, they analysed the vaccination response in 102 anti-CD20 patients. Compared to healthy controls (n = 551), all healthy controls showed serological conversion when the patient’s last anti-CD20 treatment was 1 month from vaccination, while 94% of patients did not respond, and when the patient’s last anti-CD20 treatment was 5 months from vaccination, there was a serological conversion in both patients and control groups, with no significant difference. Similarly, in Schulz’s study, naive B cells in immunocompromised haematological patients were measured to predict their humoral vaccination response. They performed anti-SARS-CoV-2 immunoassays at different intervals after the last B cell depletion treatment in 120 clinical immunocompromised hematological patients and concluded that it took at least 166 days between the last immunotherapy treatment and vaccination.For the rate of humoral immunity following SARS-CoV-2 immunization, this meta-analysis collects recent months of the literature (up to 29 October 2022) and refines the interval between the final anti-CD20 medication and vaccination. Patients treated with the final dose of anti-CD20 monoclonal antibody were divided into positive and negative groups according to whether they were infected with COVID-19 after receiving the vaccine at different times. Data on the time it takes each group of patients to receive the vaccine were collected separately, data were processed, ROC curves were made, and cut-off values were determined. B-cell depletion was also graded, and the anti-CD20 dose used when treating patients with anti-CD20 was also collected.The antibody titres of the SARS-CoV-2 vaccine were found to be significantly heterogeneous, and a subgroup analysis revealed that the duration since the last anti-CD20 treatment, the number of B cells, the dose of anti-CD20, and the disease type treated with anti-CD20 all had a significant impact on the humoral immune response rate.2 (89% vs 66%) and P value (0.21 vs 0.009) of this subgroup were significantly lower  of quickly developing knowledge databases, the current review method was constrained, making the evidence tentative rather than conclusive and necessitating future meta-analyses. In addition, no unpublished research or clinical trial registry data were checked, and no other experts on the subject were contacted. Although this is reflected in a separate meta-analysis, several potential sources of variability in the seroconversion frequencies in the study population were excluded from the subgroup analysis and were not distinguished based on the various experimental methods of detecting blood antibodies. Finally, because population-level data were insufficient for differentiating across vaccination types, we did not examine the seroconversion rates of the various vaccines provided. When evaluating the evidence base further, analyses like these are required.Click here for additional data file.


Patients with Rockall scores ≥6 have an increased risk of long-term peptic ulcer rebleeding. This study was aimed toward investigating whether an extended course of oral esomeprazole up to 1 year decreased ulcer rebleeding in such patients.n = 60) or once-daily . Thereafter, they were divided into the PPI-on-demand (n = 32) and PPI-discontinued (n = 77) subgroups. Our previous cohort with Rockall scores ≥6 served as the controls ; they received only an initial 8- to 16-week oral PPI. The primary and secondary outcomes were peptic ulcer rebleeding during the first year and the second year-and-thereafter, respectively.We prospectively enrolled 120 patients with peptic ulcer bleeding and Rockall scores ≥6. After an initial 16-week oral proton pump inhibitor (PPI) treatment, patients were randomized to receive a 36-week course of oral twice-daily esomeprazole 20 mg . The competing-risks regression analysis confirmed that extended PPI use and American Society of Anesthesiologists classification were independent factors contributing to the primary outcome. For the secondary outcome, PPI-on-demand had a borderline higher proportion of rebleeding-free than Group C ; however, only the Rockall score was the independent factor.For the primary outcome, groups D and S comprised a higher proportion of rebleeding-free than Group C .The online version contains supplementary material available at 10.1186/s12876-022-02534-0. Peptic ulcer bleeding is important in clinical practice because it is a common issue and is correlated with mortality –4. RecurThe use of proton pump inhibitors (PPIs) is the current standard treatment for peptic ulcer disease with bleeding because PPIs heal peptic ulcers well and decrease the risk of recurrent bleeding –12. HoweThis prospective study was conducted in the inpatient wards of two tertiary healthcare centers, National Cheng Kung University Hospital in Tainan City and Kaohsiung Medical University Hospital in Kaohsiung City, Taiwan from June 2015 to December 2020. The study design was approved by the National Cheng Kung University Hospital Institutional Review Board . After they provided written informed consent, the participants were enrolled. A schematic flow chart of the study protocol is summarized in Fig. Patients 20 or more years of age who were diagnosed with bleeding peptic ulcers with major stigmata of recent hemorrhage (SRH) were considered eligible. The major SRH include Forrest Ia, Ib, IIa, and IIb . At the Rockall scores ≥ 6 to define patients who were at high risk of rebleeding [In this study, we used bleeding . The parbleeding . After gbleeding , 12.Our study group had a cohort in which patients with bleeding peptic ulcer diseases and Rockall scores ≥6 from Aug 2011 to Jan 2015 were enrolled , 9. The American Society of Anesthesiologists (ASA) Physical Status classification  or pantoprazole  for 3 days . ThereafAfter the 52-week therapy, the patients in groups D and S used oral PPIs or did not at the discretion of their physicians according to their clinical needs. Thus, these patients were divided into a PPI-on-demand group and the PPI-discontinued group. The definition of PPI-discontinued was PPI use ≤3 days per week and ≤ 1 week per month. The others were defined as PPI-on-demand.Helicobacter pylori (H. pylori) infection received standard first-line or second-line eradication and all were confirmed to have successful eradication by the 13C-urea breath test [H. pylori eradication only.The patients with ath test , 19. DurThe primary and secondary outcomes were the recurrent peptic ulcer bleeding during the 1st year and the second year-and-thereafter since the first bleeding episode, respectively. All of the patients were monitored every day during hospitalization, every 2 weeks in the following 4 weeks, and every 12 weeks for the remaining weeks for a total of 1 year. They were monitored for pill counts, hemoglobin concentrations, and clinical symptoms and signs which were relevant to gastrointestinal bleeding, diarrhea, pneumonia, and bone fracture at each outpatient visit. All enrolled patients were included in the intention-to-treat (ITT) analysis, but patients who were lost to follow-up, discontinued intervention because of any reasons, had a protocol violation, or died were excluded from the per-protocol (PP) analysis for the primary endpoint. After the first year of therapy, the patients were continued to be monitored at outpatient departments every 12 weeks.Recurrent bleeding was defined as follows, including 1) the presence of hematemesis, melena, hematochezia, or bloody aspirates through a nasogastric tube, plus 2) the presence of hemodynamic instability, including systolic blood pressure < 90 mmHg, heart rate > 120 beats per minute, or a drop in hemoglobin concentration by more than 2 g/dL, or sudden increase in transfusion requirements. To confirm recurrent peptic ulcer bleeding, the hemoglobin concentration and gastroscopy were performed to check the drop in hemoglobin concentration, any blood or coffee-ground-like materials in the stomach, or the recurrence of stigmata of recent hemorrhage. The gastroscopy also confirmed whether bleeding was from a peptic ulcer or other non-ulcer lesions, such as varices. Additionally, the definition of refractory or recurrence of the ulcer was the size ≥0.5 cm.Medical events, including diarrhea and pneumonia, were monitored when patients took PPIs until 2 weeks after discontinuing PPIs. The definition of diarrhea was that the presence of loose or watery stools ≥ three times a day lasted for 1 day at least. The definition of pneumonia was the presence of one of the symptoms and signs of fever, purulent productive cough, and shortness of breath plus a typical infiltrative patch on chest X-ray. Additionally, any bone fracture, including a partial or complete break in the bone, was monitored until the last follow-up date at outpatient departments.H. pylori ulcers after eradication. The ratio of the patient number in each experiment group to the patient number in the control group was 2:5. With a two-side α value of 0.05 and power of 80% (β = 0.20), the number of patients required was 54 in each experiment group and 135 in the control group to detect a difference between the two groups. Assuming the rate of loss follow-up was 10%, sixty patients in each experimental group were enrolled. Data related to baseline characteristics and endpoints were evaluated using the one-way analysis of variance, Pearson’s χ2 test, Fisher’s exact test, or Kruskal-Wallis one-way analysis of variance by ranks. The log-rank test was used to compare the Kaplan-Meier curves among the study groups. The COX hazard regression analysis was used to evaluate the factors predicting the primary and secondary outcomes. When patients encountered death, no more chances of recurrent bleeding would be met. Thus, considering the patient’s death as a competing event, the proportional subdistribution hazards model for competing risk data according to the Fine and Gray method was used. All tests were two-tailed and P values of < 0.05 indicated significant differences. The statistical analysis was performed with SPSS software  and the competing-risks regression was evaluated using SAS software .The estimated recurrent bleeding rate during the first year in Group C was about 15% based on the previous studies , 21. We n = 60) or Group S (n = 60). The 135 patients from our previous cohort were matched into Group C   Table .Table 1BAs shown in Fig. n = 2) and terminal ovary cancer (n = 1) in Group D and multiple organ failure (n = 1) in Group S. In addition to 6 patients in Group C who died and were excluded from the per-protocol analysis, there were another 5 patients who had recurrent bleeding and died thereafter during the first year. The causes of mortality in Group C were stages IV-V chronic kidney disease with complications (n = 3), terminal cirrhosis (n = 1), septic shock in old stroke (n = 1), and disseminated cancers (n = 6). All-cause mortality rates were not significantly different between the three groups .The causes of mortality included terminal hepatoma (P = 0.21). Among these patients, the rates of the non-healed ulcers (size ≥ 0.5 cm) were not significantly different between the two groups .There were 42 patients in Group D and 48 patients in Group S who received surveillance endoscopy after the initial 16-week PPIs .During the follow-up periods, either the first year or the second year-and-thereafter, there were 1, 6, and 2 patients who had pneumonia, and 3, 2, and 12 had a bone fracture in Group D, S, and C, respectively. Additionally, 1 in Group S had pneumonia and bone fracture and 3 in Group C had diarrhea. The rates of overall medical events in the three groups were not significantly different . The rebleeding-free rates were significantly higher in Group S than in Group C by ITT analysis (P = 0.02), but borderline higher by PP analysis (P = 0.08). The rebleeding-free rates were not significantly different between Group D and Group S .During the first year, none in Group D, one in Group S, and 16 patients in Group C had recurrent peptic ulcer bleeding, respectively Table . Eleven P = 0.008, log-rank test) but not significantly different compared with Group S (P = 0.32). Moreover, the proportion of recurrent bleeding-free was higher in Group S compared with Group C .In Fig. n = 7) or having died (n = 4); thus, a total of 109 patients were still monitored. Among them, thirty-two patients received oral PPIs on-demand and 77 patients (43 from Group D and 34 from Group S) discontinued the experimental medication and did not take any other PPIs. In addition, 116 patients in Group C continued to be monitored during this period after excluding those lost to follow-up (n = 1), PPIs use (n = 7) and those having died during the first year .The median  follow-up period from the first bleeding episode was 1650 (1090.8–1882.5) days in the PPI-on-demand group, 900 (582–1465.5) days in the PPI-discontinued group, and 1728.5 (658–2645.5) days in Group C, respectively , but there was not a significant difference between the PPI-discontinued subgroup and Group C .Eventually, two patients 6.3%) among the patients with PPIs on-demand, 11 (14.3%) in the PPI-discontinued group, and 24 (20.7%) in Group C had recurrent peptic ulcer bleeding during the second year-and-thereafter (Table % among tH. pylori infection at enrollment (Table H. pylori eradication (P = 0.78). Finally, a total of seven patients did not receive H. pylori eradication; moreover, none of them had recurrent bleeding either during the first year or during the second year-and-thereafter.Among the patients who were diagnosed with nt Table , eleven P = 0.003) and extended PPI use (P = 0.03) remained as the independent factors.The COX hazard regression model was used to evaluate the independent factors predicting the primary outcome. The PPI use in groups D and S was combined to serve as the extended PPI use group. The univariable analysis showed the ASA classification, Rockall scores, and extended PPI use correlated to the primary outcome. Furthermore, the COX hazard regression analyses proved that the ASA classification and extended PPI use were two independent factors contributing to the primary outcome in the ITT and PP analyses Table . After aP = 0.001 and 0.02, respectively, Table For the secondary outcome, the multivariable COX hazard regression and the proportional subdistribution hazards model showed that the Rockall score was the only independent factor (This study demonstrated that an extended course of oral esomeprazole 20 mg for 36 weeks in either a twice- or once-daily manner after an initial 16-week PPI therapy could protect patients with Rockall scores ≥ 6 from delayed recurrent peptic ulcer bleeding. However, such protective effects tended to diminish after PPIs were discontinued thereafter.H. pylori infection is one of the major causes of recurrent peptic ulcers, and H. pylori eradication should be performed if H. pylori infection is confirmed [H. pylori-infected patients received H. pylori eradication. Only seven patients didn’t receive eradication therapy; however, none of them encountered recurrent ulcer bleeding during the follow-up periods. Nevertheless, over the past decades, H. pylori-negative peptic ulcer has become an emerging issue because of the high recurrent bleeding risk [H. pylori-negative ulcers were elderly and had underlying comorbidities [Although a 4- to 8-week treatment of PPIs can heal more than 90% of peptic ulcers , there wonfirmed , 19. In ing risk , 23, 25.bidities , 23, 26;bidities , 14, 27.During the second year-and-thereafter, the COX hazard regression model or the competing-risks regression analyses showed that only the Rockall score was correlated with recurrent bleeding, and not on-demand PPIs or PPI discontinuation Table . These fThere is concern about the benefits and risks of long-term PPI use , 30, 31.The present study had limitations. First, we did not design a parallel-control group to receive a placebo because of ethics concerns. Nevertheless, we used the data from a historical control group. The controls had similar baseline characteristics except for the distribution of Rockall scores and the ASA classification. After adjusting for these two possible confounders, extended PPI use was an independent factor by which to predict the primary outcome. Thus, the bias due to a non-parallel-group design for the controls was reduced. Second, the dropout rate in the experimental groups was higher than expected because the PPI use was interrupted by multiple medical events. Nevertheless, the significant between-group differences in the primary outcomes decreased the concern of a type II error. Third, the sample size was limited to evaluate the secondary outcome; thus, further study is needed. Fourth, genotyping tests for CYP2C19 alleles were not conducted in this study. Nevertheless, all groups shared a similar fair condition. Moreover, no change in dosing of esomeprazole was recommended for various CYP2C19 metabolizers because evidence of different treatment outcome was insufficient .In conclusion, patients with Rockall scores ≥6 using an extended course of oral esomeprazole 20 mg in an either twice- or once-daily manner up to 1 year after ulcer bleeding exhibited a lower cumulative risk of recurrent ulcer bleeding as compared to those using an 8- to 16-week course of oral PPIs. However, the protective effect of reducing recurrent peptic ulcer bleeding after shifting to on-demand or discontinuing the use of PPIs needed to be further validated.Additional file 1: Supplementary Table 1. The parameters of the Rockall score.Additional file 2: Supplementary Table 2. American Society of Anesthesiologists Physical Status classification system.


To explore the predictors of mucosal healing (MH) for short- and long-term after exclusive enteral nutrition (EEN) in pediatric Crohn’s disease (CD) patients.A retrospective analysis was performed for newly diagnosed active CD patients admitted to our center from January 2017 to 30 December 2020, who were treated with EEN for induction therapy with a minimum of 12 months of follow-up post-EEN. According to the simple endoscopic score for CD (SES-CD), at 1-year post-EEN, 17 patients with an SES-CD < 3 were classified into the sustained MH group (sMH), and 33 patients with an SES-CD ≥ 3 were classified into the sustained non-MH group (sNMH). Statistical methods were used to compare the differences between the two groups and explore the predictors of MH at the end of EEN and 1-year post-EEN.p < 0.001 at baseline; 1.0 (3.5) vs. 4.0 (2.0), respectively, p < 0.01 at the end of EEN]. The weighted Pediatric Crohn’s Disease Activity Index and erythrocyte sedimentation rate in the sMH group were lower than those in the sNMH group at baseline (both p < 0.05), but showed no difference at the end of EEN. From baseline to 1-year post-EEN, compared with patients in the sNMH group, there were more patients classified with L1 in the sMH group at each time point  and fewer patients classified with L3 in the sMH group at baseline and 1-year post-EEN. After EEN, fewer patients received infliximab and had a longer exposure time to infliximab in the sMH group than in the sNMH group. Only the SES-CD at baseline was negatively associated with MH at the end of EEN  and 1-year post-EEN , and the cut off value was 11.5.The SES-CD in the sMH group was lower than that in the sNMH group both at baseline and the end of EEN [sMH vs. sNMH: 8.7 ± 1.2 vs. 16.2 ± 1.0, respectively, The SES-CD could predict both short- and long-term MH for EEN. Patients with an SES-CD < 11.5 had a high probability of reaching MH by EEN-inducing therapy and maintaining sustained MH at 1-year post-EEN. Patients with an SES-CD greater than 11.5 at baseline should be treated more aggressively with biologics. Exclusive enteral nutrition (EEN) has been widely studied and recommended as a first-line therapy for inducing remission of Crohn’s disease (CD) in children , 2. MostMucosal healing (MH) is a treatment target for CD patients. The 2020 European Crohn’s and Colitis Organization-Pediatric IBD Porto group of the European Society of Pediatric Gastroenterology, Hepatology and Nutrition guideline defined MH as the absence of macroscopic inflammation or a simple endoscopic score for CD (SES-CD) < 3 points . For CD Crohn’s disease is characterized by periods of remission and relapse, and the anti-inflammatory effect of EEN on the gut of CD patients is rapidly lost after food reintroduction , 17. TheTherefore, we designed this study. First, we identified the characteristics and clinical differences between patients with sustained MH and those with sustained non-MH at 1-year post-EEN. Second, we explored the predictive factors of MH for EEN at the end of EEN (short-term) and 1-year post-EEN (long-term).A retrospective analysis was performed for newly diagnosed active CD patients admitted to our center from January 2017 to 30 December 2020, who were treated with EEN for induction therapy with a minimum of 12 months of follow-up post-EEN. CD was diagnosed according to the Porto criteria  and basethrough a nasogastric tube.The feeding protocol was as follows: patients were exclusively treated with EEN for at least 6 weeks with no other medication. The formula could be polymeric or oligomeric, and the volume was determined according to the patient’s energy needs. The patients received high-energy intakes (>110–120% of the average requirement). For children ≤ 6 years old, the energy intakes were calculated according to weight; for children > 6 years old, the energy intakes were calculated according to age and sex . No otheThe exclusion criteria were as follows: (1) patients who had genetic mutations or those with CD combined with another enteropathy, such as an Epstein–Barr virus or a tuberculosis infection; (2) patients who did not finish the daily prescribed volume of formula for any reason; (3) patients who had been given corticosteroids, immunosuppressive drugs, or biological agents before or during the EEN therapy process; and (4) patients with missing baseline, end of EEN, or 1-year post-EEN endoscopic imaging data.A total of 184 active CD patients were newly diagnosed from 2017.01 to 2020.12.31 ; 67 patiThe medical records of these 50 patients from baseline (within 1 week before the start of EEN) to 2021.12.31 (at least 12 months of follow-up post-EEN) were extracted from existing hospital databases, including patient characteristics, disease activity data such as the SES-CD, Paris Classifications, Lewis score, wPCDAI, FCP, and erythrocyte sedimentation rate (ESR), nutrient data such as weight, height, serum albumin (ALB) level, hemoglobin (Hgb) level, and maintenance treatment post-EEN.t-test was used to analyze the differences. Otherwise, skewed quantitative variables are expressed as medians [interquartile range (IQR)], and the Mann–Whitney test was used to analyze the differences. Univariate and multivariate logistic regression models were performed to identify potential predictors. All the variables included in p < 0.05) in the univariate analysis and based on theoretical or empirical knowledge were considered to be related to the dependent variable and included in the multivariate analysis, as shown in p < 0.05 was regarded as statistically significant.Data were analyzed using SPSS 26.0  and GraphPad Prism Software . Categorical variables are expressed as numbers and proportions (%), and Fisher’s exact test was used to analyze the differences. Normally distributed quantitative variables are expressed as the means ± SD, and Student’s The demographic and clinical data of all patients in the two groups at baseline and at the end of EEN are summarized in p < 0.001 at baseline; 1.0 (3.5) vs. 4.0 (2.0), respectively, p < 0.01 at the end of EEN] (p = 0.04 at baseline)  .p = 0.02 at baseline) (p < 0.01 at baseline) (There were no significant differences in FCP or Hgb levels between the two groups at baseline or at the end of EEN . The ESRaseline) . The ALBaseline) .p < 0.001 at baseline; 11 (64.7%) vs. 4 (12.1%), respectively, p < 0.001 at the end of EEN; 12 (70.6%) vs. 1 (3.0%), respectively, p < 0.001 at 1-year post-EEN]. In the sMH group, the number of patients classified with L3 decreased during follow-up. However, in the sNMH group, patients classified with L3 decreased at the end of EEN but increased again at 1-year post-EEN during follow up, so there were fewer patients classified with L3 in the sMH group at baseline and at 1-year post-EEN, but no difference was shown at the end of EEN compared with the sNMH group . There were no differences in patients classified with L2 .For azathioprine (AZA)/MTX usage, there were no differences in the percentage of patients  or time  = 0.01] , and thep = 0.00 in the multivariate model)  .p = 0.001 in the multivariate model), and other variables were finally not included in the multivariate analysis    . At 1-ye71–0.95) .p = 0.002]. Two patients received IFX in the sMH group, and 13 patients received anti-TNF therapy  . No patients in the sMH group needed surgery, but two patients in the sNMH group received surgery therapy.Nine patients in the sMH group and 15 in the sNMH group completed the 2-year follow-up. Among them, eight patients maintained MH in the sMH group, and only three patients reached MH in the sNMH group 131). Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.YH, YW, and WT contributed to the design of the study and interpretation of data. WT, WH, and PS performed the statistical analysis. WT, ZY, JW, and YZ performed the acquisition of data. WT drafted the manuscript. YH critically revised the manuscript for important intellectual content. All authors reviewed and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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